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Layered Coding Basic Overview
21

Layered Coding

Dec 31, 2015

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Joel Lloyd

Layered Coding. Basic Overview. Outline. Pyramidal Coding Scalability in the Standard Codecs Layered Coding with Wavelets Conclusion. Laplacian w/ Gaussian Pyramids. Laplacian w/ DCT Coefficient Pyramids. DCT Pyramid Example. Figure 7.5. Reconstruction Data for Fig. 7.5. - PowerPoint PPT Presentation
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Page 1: Layered Coding

Layered Coding

Basic Overview

Page 2: Layered Coding

Outline

Pyramidal Coding

Scalability in the Standard Codecs

Layered Coding with Wavelets

Conclusion

Page 3: Layered Coding

Laplacian w/ Gaussian Pyramids

Page 4: Layered Coding

Laplacian w/ DCT Coefficient Pyramids

Page 5: Layered Coding

DCT Pyramid Example

Figure 7.5

Page 6: Layered Coding

Reconstruction Data for Fig. 7.5

Page 7: Layered Coding

Scalability in the Standard Codecs

Data Partitioning

Signal-to-Noise Ratio (SNR)

Spatial

Temporal

Page 8: Layered Coding

Data Partitioning

Page 9: Layered Coding

SNR Scalable Coder

Page 10: Layered Coding

SNR Scalability – no drift

Page 11: Layered Coding

Spatial Scalability

Page 12: Layered Coding

Temporal Scalability

Page 13: Layered Coding

Scalability Applications

Data Partitioning– Video of ATM networks

SNR– Transmission of video at different qualities

Video on demand, simultaneous TV and enhanced TV

– Video over high packet loss networks (Internet)

Spatial Scalability– Internetworking between two different standards– Simulcasting of drift-free video (TV & HDTV)

Page 14: Layered Coding

Scalability Applications

Spatial Scalability (continued)– Reception of low spatial resolution pictures over

mobile networks

Temporal Scalability– Migration to HDTV from current interlaced– Internetworking between mobile and fixed networks

Page 15: Layered Coding

Layered Coding with Wavelets

Growing interest due to new efficient coding techniques (Embedded Zero-tree Wavelets, or EZW)

Accepted for coding of still images– MPEG-4 and JPEG 2000

Predicted to continues in growth

Page 16: Layered Coding

Discrete Wavelet Transform

Split signal spectrum into several frequency bands analysis filters

Figs. 7.27, 7.28, 7.29

Page 17: Layered Coding

Distortions

Page 18: Layered Coding

Filter Bank Solutions

Page 19: Layered Coding

Higher Order Systems

Multiple wavelet transform coding by means of repeated two-band splits

Page 20: Layered Coding

Further Considerations

• Wavelet Example – Fig. 7.32

• Zero-Tree Coding – Fig. 7.34

• Quad-Tree Representation- Bands look like scaled versions of each other- Lower bands have 0.25 dimension of higher

Page 21: Layered Coding

Conclusion

Layered coding facilitates– Error protection– Efficient use of resources– Multiple services– Customer satisfaction